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The FORMOSAT-7/COSMIC-2 (simplified as FORMOSAT-7 in the following descriptions) is a major collaborative space program between Taiwan and the U.S. In this collaborative program, the designated representative for Taiwan is NSPO (National Space Organization) and the designated representative for the U.S. is NOAA (National Oceanic and Atmospheric Administration). The FORMOSAT-7 program is a follow-on program to the successful FORMOSAT-3/COSMIC program with upgraded performance for spacecraft bus and mission payload.
The FORMOSAT-7 program calls for 12 mission specific satellites plus one NSPO-built satellite. The 12-satellites are planned to be launched and deployed in two clusters of 6-satellites into the designated low and high inclination orbits in 2016 and 2018, respectively. The NSPO-Built satellite that is planned to be launched in the second cluster will enhance the utility of the FORMOSAT-7 constellation and will serve as the space qualification platform for the self-reliant key components for the future standard bus of this class. The mission architecture is as shown below:

▲ FORMOSAT-7 Mission Architecture

Each FORMOSAT-7 satellite is equipped with a Radio Occultation (RO) receiver,called TGRS, that receives the GNSS signal from GPS, GLONASS, or GALLIELO satellites. The received radio occultation data is then transmitted down to the ground to retrieve and process into useful atmospheric and ionosheric weather data such as temperature, pressure, water vapor content, electron density, etc. The FORMOSAT-7 constellation can provide 8000 atmospheric soundings per day, data which will contribute to weather forecasts and climate observations. The data distribution simulation for 24-hr coverage by FORMOSAT-7 constellation is shown below:

The first 6-satellites are designed for observing the lower inclination planes to cover the equatorial regions between 50° south and 50° north latitudes. FORMOSAT-7 RO data provides the needed effective weather data to CWB, and post data analysis indicated that the typhoon track prediction accuracy can be dramatically improved.